Zobrazeno 1 - 10
of 1 265
pro vyhledávání: '"Konin, A."'
Autor:
Besrour, Marwan, Lavoie, Jacob, Omrani, Takwa, Martin-Hardy, Gabriel, Koleibi, Esmaeil Ranjbar, Menard, Jeremy, Koua, Konin, Marcoux, Philippe, Boukadoum, Mounir, Fontaine, Rejean
The computational complexity of deep learning algorithms has given rise to significant speed and memory challenges for the execution hardware. In energy-limited portable devices, highly efficient processing platforms are indispensable for reproducing
Externí odkaz:
http://arxiv.org/abs/2408.07734
Autor:
Koleibi, Esmaeil Ranjbar, Koua, Konin, Lemaire, William, Benhouria, Maher, Besrour, Marwan, Omrani, Takwa, Ménard, Jérémy, Gauthier, Louis-Philippe, Dridi, Montassar, Mazandarani, Mahziar Serri, Gosselin, Benoit, Fontaine, Sébastien Royand Réjean
This paper presents a compact low-power, low-noise bioamplifier for multi-channel electrode arrays, aimed at recording action potentials. The design we put forth attains a notable decrease in both size and power consumption. This is achieved by incor
Externí odkaz:
http://arxiv.org/abs/2406.17779
Autor:
Hyder, Syed Waleed, Usama, Muhammad, Zafar, Anas, Naufil, Muhammad, Fateh, Fawad Javed, Konin, Andrey, Zia, M. Zeeshan, Tran, Quoc-Huy
This paper presents a 2D skeleton-based action segmentation method with applications in fine-grained human activity recognition. In contrast with state-of-the-art methods which directly take sequences of 3D skeleton coordinates as inputs and apply Gr
Externí odkaz:
http://arxiv.org/abs/2309.06462
Autor:
Konin V.V.
Publikováno v:
Пенитенциарная наука, Vol 18, Iss 3 (67), Pp 256-262 (2024)
Introduction: the right to receive qualified legal assistance is enshrined in Article 48 of the Constitution of the Russian Federation. It is the right of everyone who is subject to criminal prosecution, regardless of the financial situation of the p
Externí odkaz:
https://doaj.org/article/283ea70f6ef245048006adcfa466d413
Autor:
Lobanov, Aleksandr, Veprikov, Andrew, Konin, Georgiy, Beznosikov, Aleksandr, Gasnikov, Alexander, Kovalev, Dmitry
Distributed optimization has a rich history. It has demonstrated its effectiveness in many machine learning applications, etc. In this paper we study a subclass of distributed optimization, namely decentralized optimization in a non-smooth setting. D
Externí odkaz:
http://arxiv.org/abs/2307.00392
Autor:
Tran, Quoc-Huy, Mehmood, Ahmed, Ahmed, Muhammad, Naufil, Muhammad, Zafar, Anas, Konin, Andrey, Zia, M. Zeeshan
This paper presents an unsupervised transformer-based framework for temporal activity segmentation which leverages not only frame-level cues but also segment-level cues. This is in contrast with previous methods which often rely on frame-level inform
Externí odkaz:
http://arxiv.org/abs/2305.19478
Autor:
Tran, Quoc-Huy, Ahmed, Muhammad, Popattia, Murad, Ahmed, M. Hassan, Konin, Andrey, Zia, M. Zeeshan
This paper presents a self-supervised temporal video alignment framework which is useful for several fine-grained human activity understanding applications. In contrast with the state-of-the-art method of CASA, where sequences of 3D skeleton coordina
Externí odkaz:
http://arxiv.org/abs/2305.19480
Autor:
Francis Amankwah, Frederick Kwaku Sarfo, Michael Osei Aboagye, Daniel Konin, Raphael Kwasi Dzakpasu
Publikováno v:
Education Inquiry, Vol 15, Iss 3, Pp 312-332 (2024)
A cross-sectional survey was conducted to explore university teachers’ stages of concerns (SoC) about the adoption of the Moodle LMS at the Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development (AAMUSTED), Ghana. Hundre
Externí odkaz:
https://doaj.org/article/b2bdd61f713f4b43b1035326a850b019
Publikováno v:
Eng, Vol 5, Iss 2, Pp 750-783 (2024)
This comprehensive literature review investigates the impact of stabilization and reinforcement techniques on the mechanical, hygrothermal properties, and durability of adobe and compressed earth blocks (CEBs). Recent advancements in understanding th
Externí odkaz:
https://doaj.org/article/26d05ecf80744cbab06b77f0727af93f
Autor:
Khan, Hamza, Haresh, Sanjay, Ahmed, Awais, Siddiqui, Shakeeb, Konin, Andrey, Zia, M. Zeeshan, Tran, Quoc-Huy
We introduce a novel approach for temporal activity segmentation with timestamp supervision. Our main contribution is a graph convolutional network, which is learned in an end-to-end manner to exploit both frame features and connections between neigh
Externí odkaz:
http://arxiv.org/abs/2206.15031